Données spatiales

Packages historique

• rgdal: interface entre R and GDAL (Geospatial Data Abstraction Library) and PROJ4 librarie: raster / vector

• sp: classes d’objets spatiaux pour R. (S4)

• rgeos: interface entre R et GEOS (Geometry Engine - Open Source) library: area, perimeter, distances, dissolve, buffer, overlap, union, contains…

Toujours utilisé

Simple Features for R

• sf Website: Simple Features for R Octobre 2016

• sp, rgeos and rgdal tout dans le même package

• Plus simple

• Tidy data: compatible dplyr.

Simple Features for R

sf objects data structure:

• metadata
• geom column avec des géomtrie stockées au format Well-known_text (wkt)

Lire des données

Capable de lire n’importe quel format de données spatiale : shp, geojson, kml

library(sf)
mtq <- st_read("data/mtq/martinique.shp")

class(mtq)

## [1] "sf"         "data.frame"

str(mtq)

## Classes 'sf' and 'data.frame':   34 obs. of  24 variables:
##  $ INSEE_COM: Factor w/ 34 levels "97201","97202",..: 1 2 3 4 5 6 7 8 9 10 ...
##  $ STATUT   : Factor w/ 3 levels "Commune simple",..: 1 1 1 1 1 1 1 1 2 1 ...
##  $ LIBGEO   : Factor w/ 34 levels "Basse-Pointe",..: 9 23 1 11 3 12 4 5 6 13 ...
##  $ P13_POP  : num  1830 3929 3565 3742 4464 ...
##  $ C13_POP  : num  1482 3190 2983 3157 3513 ...
##  $ C13_CS1  : num  9.78 97.43 39.51 80.13 36.14 ...
##  $ C13_CS2  : num  48.9 170.5 98.8 192.3 172.7 ...
##  $ C13_CS3  : num  9.78 109.61 43.46 84.14 349.33 ...
##  $ C13_CS4  : num  103 240 182 341 518 ...
##  $ C13_CS5  : num  274 560 569 533 675 ...
##  $ C13_CS6  : num  289 386 565 260 317 ...
##  $ C13_CS7  : num  430 747 941 990 735 ...
##  $ C13_CS8  : num  318 881 545 677 711 ...
##  $ P08_POP  : num  1691 3826 3804 3760 4515 ...
##  $ C08_POP  : num  1347 3068 3054 3039 3454 ...
##  $ C08_CS1  : num  31.4 49 44.5 88.9 32.8 ...
##  $ C08_CS2  : num  43.2 144 106.8 129.4 155.7 ...
##  $ C08_CS3  : num  11.8 65.3 27.7 153.6 262.2 ...
##  $ C08_CS4  : num  145 216 186 408 615 ...
##  $ C08_CS5  : num  224 600 448 509 729 ...
##  $ C08_CS6  : num  251 459 620 271 332 ...
##  $ C08_CS7  : num  381 559 882 832 549 ...
##  $ C08_CS8  : num  259 975 739 646 778 ...
##  $ geometry :sfc_POLYGON of length 34; first list element: List of 1
##   ..$ : num [1:55, 1:2] 699261 699226 699016 698406 698001 ...
##   ..- attr(*, "class")= chr  "XY" "POLYGON" "sfg"
##  - attr(*, "sf_column")= chr "geometry"
##  - attr(*, "agr")= Factor w/ 3 levels "constant","aggregate",..: NA NA NA NA NA NA NA NA NA NA ...
##   ..- attr(*, "names")= chr  "INSEE_COM" "STATUT" "LIBGEO" "P13_POP" ...

Changer la projection ou passer en lat/long

mtq_rp = st_transform(mtq,4326)
mtq_rp

## Simple feature collection with 34 features and 23 fields
## geometry type:  POLYGON
## dimension:      XY
## bbox:           xmin: -61.2291 ymin: 14.39456 xmax: -60.8095 ymax: 14.8781
## epsg (SRID):    4326
## proj4string:    +proj=longlat +datum=WGS84 +no_defs
## First 10 features:
##    INSEE_COM               STATUT            LIBGEO P13_POP   C13_POP
## 1      97201       Commune simple L'Ajoupa-Bouillon    1830  1481.801
## 2      97202       Commune simple Les Anses-d'Arlet    3929  3190.115
## 3      97203       Commune simple      Basse-Pointe    3565  2983.215
## 4      97204       Commune simple         Le Carbet    3742  3157.044
## 5      97205       Commune simple       Case-Pilote    4464  3513.386
## 6      97206       Commune simple        Le Diamant    6063  4766.876
## 7      97207       Commune simple             Ducos   17051 14032.139
## 8      97208       Commune simple Fonds-Saint-Denis     813   684.000
## 9      97209 Préfecture de région    Fort-de-France   84174 68712.330
## 10     97210       Commune simple       Le François   18225 14959.798
##       C13_CS1    C13_CS2     C13_CS3   C13_CS4    C13_CS5   C13_CS6    C13_CS7
## 1    9.780866   48.90433    9.780866  102.6991   273.8642  288.5355   430.3581
## 2   97.433459  170.50855  109.612642  239.5239   560.2424  385.6741   746.5743
## 3   39.510829   98.77707   43.461911  181.7498   568.9559  565.0048   940.5055
## 4   80.133275  192.31986   84.139939  340.5664   532.8800  260.4331   989.5457
## 5   36.137682  172.65782  349.330931  517.9734   674.5701  317.2085   734.7995
## 6   28.374581  251.31772  397.190830  802.5953   835.0234  506.6890   956.6287
## 7   85.296622  614.27717  772.462370 2016.3061  2716.9554 1548.7246  2936.4613
## 8   32.000000   16.00000   12.000000   68.0000   112.0000  100.0000   224.0000
## 9   86.572838 2720.48912 4000.386802 8407.4236 13799.2254 7309.1357 16184.2574
## 10 137.873479  817.80956  544.951619 1470.5494  2966.3701 2115.8299  3577.5536
##       C13_CS8 P08_POP   C08_POP   C08_CS1    C08_CS2    C08_CS3   C08_CS4
## 1    317.8781    1691  1346.519  31.40569   43.18282   11.77713  145.2513
## 2    880.5453    3826  3067.742  49.00453  143.95079   65.33937  216.3534
## 3    545.2494    3804  3054.108  44.51803  106.84327   27.70011  186.0292
## 4    677.0259    3760  3038.656  88.93759  129.36377  153.61948  408.2622
## 5    710.7078    4515  3453.848  32.77765  155.69385  262.22121  614.5810
## 6    989.0568    5850  4569.721  33.41790  329.82460  338.35626  676.7125
## 7   3341.6553   16433 13441.442 106.52838  563.35180  629.34551 1785.4747
## 8    120.0000     873   708.000  16.00000   16.00000   16.00000   48.0000
## 9  16204.8388   89000 71566.825 119.06082 2480.10528 3976.89825 8630.6045
## 10  3328.8607   19189 15209.492 132.46653  666.44376  614.97272 1359.9284
##       C08_CS5   C08_CS6    C08_CS7    C08_CS8                       geometry
## 1    223.7655  251.2455   380.7940   259.0969 POLYGON ((-61.14848 14.8059...
## 2    600.3054  459.4174   558.8020   974.5694 POLYGON ((-61.0533 14.45579...
## 3    448.1481  620.2845   881.5853   738.9993 POLYGON ((-61.0846 14.85312...
## 4    509.2011  270.7288   832.0621   646.4813 POLYGON ((-61.16765 14.6753...
## 5    729.2055  331.8737   549.0257   778.4692 POLYGON ((-61.11754 14.6275...
## 6    760.2573  563.9271   743.5483  1123.6770 POLYGON ((-61.0533 14.45579...
## 7   2786.1717 1549.6171  2378.2314  3642.7213 POLYGON ((-60.954 14.55508,...
## 8    104.0000  124.0000   200.0000   184.0000 POLYGON ((-61.11316 14.7019...
## 9  15437.6017 7964.5133 15996.5794 16961.4616 POLYGON ((-61.0392 14.64185...
## 10  3079.8702 2219.3613  3277.7336  3858.7154 POLYGON ((-60.89389 14.6500...

Système de coordonées

Les projections/système de coordonées sont répertoriées grâce à un code le code epsg :

• lat/long : 4326 https://epsg.io/4326
• Lambert 93 : 2154 https://epsg.io/2154
• Pseudo-Mercator : 3857 https://epsg.io/3857
• Lambert azimuthal equal area : 3035 https://epsg.io/3035

Préservations ? angles, aires, distance locales, …

Affichage

plot(mtq)

Affichage, seulement la géométrie

plot(st_geometry(mtq))

Suppression de la géométrie

mtq %>% st_drop_geometry()

##    INSEE_COM               STATUT            LIBGEO P13_POP    C13_POP
## 1      97201       Commune simple L'Ajoupa-Bouillon    1830  1481.8012
## 2      97202       Commune simple Les Anses-d'Arlet    3929  3190.1148
## 3      97203       Commune simple      Basse-Pointe    3565  2983.2154
## 4      97204       Commune simple         Le Carbet    3742  3157.0443
## 5      97205       Commune simple       Case-Pilote    4464  3513.3858
## 6      97206       Commune simple        Le Diamant    6063  4766.8763
## 7      97207       Commune simple             Ducos   17051 14032.1389
## 8      97208       Commune simple Fonds-Saint-Denis     813   684.0000
## 9      97209 Préfecture de région    Fort-de-France   84174 68712.3297
## 10     97210       Commune simple       Le François   18225 14959.7983
## 11     97211       Commune simple     Grand'Rivière     583   518.4111
## 12     97212       Commune simple        Gros-Morne   10012  8291.2642
## 13     97213       Commune simple       Le Lamentin   40040 32027.1180
## 14     97214       Commune simple        Le Lorrain    7177  5980.0000
## 15     97215       Commune simple           Macouba    1090   892.5087
## 16     97216       Commune simple        Le Marigot    3481  2963.1131
## 17     97217      Sous-préfecture          Le Marin    8543  6664.9936
## 18     97218       Commune simple    Le Morne-Rouge    5021  4086.3533
## 19     97219       Commune simple       Le Prêcheur    1632  1321.4080
## 20     97220       Commune simple    Rivière-Pilote   12359 10226.8721
## 21     97221       Commune simple     Rivière-Salée   12737 10018.1007
## 22     97222       Commune simple         Le Robert   23296 18507.5496
## 23     97223       Commune simple      Saint-Esprit    9524  7695.7080
## 24     97224       Commune simple      Saint-Joseph   16885 13620.8735
## 25     97225      Sous-préfecture      Saint-Pierre    4285  3469.1633
## 26     97226       Commune simple       Sainte-Anne    4436  3650.1201
## 27     97227       Commune simple       Sainte-Luce    9991  8099.6994
## 28     97228       Commune simple      Sainte-Marie   17188 14241.0491
## 29     97229       Commune simple        Schoelcher   19922 16614.2363
## 30     97230      Sous-préfecture        La Trinité   13253 10572.2203
## 31     97231       Commune simple   Les Trois-Îlets    7698  6160.4195
## 32     97232       Commune simple        Le Vauclin    9097  7484.0000
## 33     97233       Commune simple     Le Morne-Vert    1877  1576.6418
## 34     97234       Commune simple     Bellefontaine    1568  1244.0000
##       C13_CS1     C13_CS2     C13_CS3    C13_CS4     C13_CS5    C13_CS6
## 1    9.780866   48.904329    9.780866  102.69909   273.86424  288.53554
## 2   97.433459  170.508554  109.612642  239.52392   560.24239  385.67411
## 3   39.510829   98.777071   43.461911  181.74981   568.95593  565.00485
## 4   80.133275  192.319860   84.139939  340.56642   532.88002  260.43314
## 5   36.137682  172.657816  349.330931  517.97345   674.57007  317.20855
## 6   28.374581  251.317719  397.190830  802.59530   835.02339  506.68895
## 7   85.296622  614.277170  772.462370 2016.30614  2716.95542 1548.72465
## 8   32.000000   16.000000   12.000000   68.00000   112.00000  100.00000
## 9   86.572838 2720.489119 4000.386802 8407.42359 13799.22537 7309.13571
## 10 137.873479  817.809557  544.951619 1470.54935  2966.37006 2115.82989
## 11   8.498542    8.498542    0.000000   29.74490    84.98542   93.48397
## 12  87.680236  348.176203  117.594628  775.34763  1646.66063 1225.49544
## 13 105.134620 1394.623448 1987.809553 4467.33585  6767.07147 3829.16288
## 14 140.000000  212.000000   84.000000  356.00000  1056.00000  976.00000
## 15   3.797909   15.191638    3.797909   37.97909   136.72474  212.68293
## 16  21.052313   89.472331   42.104627  273.68007   478.94013  473.67705
## 17  47.947972  255.726938  211.783472  755.19824  1218.70857  835.10269
## 18  93.329084  201.394339   54.032628  371.73749   711.63199  628.74330
## 19  35.493065   31.549391    3.943674   90.70450   232.67676  212.95839
## 20 102.664033  441.779628  137.740661  831.63454  2128.10894 1385.38721
## 21  55.159184  437.708811  482.066415 1315.36217  2094.37108 1178.62565
## 22 109.836295  726.630357  755.613487 2182.43356  3754.08227 2687.21168
## 23 137.102386  253.881290  304.852245  889.15238  1391.32750  965.36544
## 24  65.074403  559.494607  678.745732 1788.00192  2601.94765 1823.61477
## 25  86.494739  152.637774   91.582664  339.87344   572.57468  361.24273
## 26  56.505102  208.555193  132.530147  336.97588   639.02133  485.83444
## 27  70.655988  578.369727  403.748500 1181.97373  1540.30053  864.02179
## 28 180.337051  490.843956  200.404618 1187.24653  2406.03624 2108.33487
## 29  44.419169  780.708185 1756.684719 2727.91907  2794.04105 1158.67612
## 30  89.839442  368.103065  623.619347 1349.43827  2112.97113 1168.16531
## 31  16.236905  393.626072  621.002172  888.73280  1120.16812  551.99533
## 32 168.000000  344.000000  196.000000  784.00000  1148.00000  652.00000
## 33  63.860507   79.825633   47.895380  175.61639   279.38972  171.62511
## 34  36.000000   48.000000   32.000000  184.00000   184.00000  232.00000
##       C13_CS7    C13_CS8 P08_POP   C08_POP    C08_CS1    C08_CS2    C08_CS3
## 1    430.3581   317.8781    1691  1346.519  31.405688   43.18282   11.77713
## 2    746.5743   880.5453    3826  3067.742  49.004525  143.95079   65.33937
## 3    940.5055   545.2494    3804  3054.108  44.518027  106.84327   27.70011
## 4    989.5457   677.0259    3760  3038.656  88.937594  129.36377  153.61948
## 5    734.7995   710.7078    4515  3453.848  32.777652  155.69385  262.22121
## 6    956.6287   989.0568    5850  4569.721  33.417902  329.82460  338.35626
## 7   2936.4613  3341.6553   16433 13441.442 106.528379  563.35180  629.34551
## 8    224.0000   120.0000     873   708.000  16.000000   16.00000   16.00000
## 9  16184.2574 16204.8388   89000 71566.825 119.060817 2480.10528 3976.89825
## 10  3577.5536  3328.8607   19189 15209.492 132.466525  666.44376  614.97272
## 11   161.4723   131.7274     751   635.557   9.930579   19.86116    0.00000
## 12  2278.6241  1811.6853   10734  8644.872 127.304900  294.45494  182.32140
## 13  6571.0609  6904.9193   39410 30843.896 101.877950 1292.62883 1652.86865
## 14  1896.0000  1260.0000    7650  6228.000 196.000000  176.00000   68.00000
## 15   284.8432   197.4913    1284  1009.910  15.718439   23.57766    0.00000
## 16   931.5649   652.6217    3668  3009.328  12.216486   89.58757   36.64946
## 17  1618.3502  1722.1755    8954  6748.948  25.054350  225.48915  233.84060
## 18  1203.0656   822.4189    5150  4088.748  77.528696  142.81602   67.95410
## 19   311.7720   402.3102    1682  1277.592 101.847039   31.33755   11.75158
## 20  2363.5260  2836.0311   13617 10770.916  69.857243  436.85120  144.84662
## 21  2104.7438  2350.0636   12968  9980.573  67.247838  464.84423  407.52675
## 22  3839.5539  4452.1881   23903 18726.445 183.991915  691.81324  715.08916
## 23  1895.2591  1858.7676    9045  7170.159  93.014297  279.04289  232.53574
## 24  3309.7225  2794.2719   16966 13612.124  67.350778  534.14049  654.29614
## 25  1059.0207   805.7366    4496  3554.202  56.778156  186.55680   85.16723
## 26   962.6415   828.0566    4833  3806.386  53.437380  234.30236   90.43249
## 27  1823.8962  1636.7329    9424  7598.989  42.801686  513.62023  440.66281
## 28  3996.2112  3671.6347   19056 15246.407 169.852571  510.08977  142.60018
## 29  3735.6264  3616.1615   21737 17877.768  39.652508  854.68783 1668.64685
## 30  2676.1019  2183.9818   13802 10878.932 106.154507  428.26444  709.30370
## 31  1347.3065  1221.3516    7368  5778.766  20.815624  353.86560  562.02184
## 32  2152.0000  2040.0000    8947  7192.000 136.000000  196.00000  180.00000
## 33   423.0759   335.3532    1853  1548.475  63.690481   67.67114   55.72917
## 34   260.0000   268.0000    1454  1100.000  32.000000   44.00000   32.00000
##       C08_CS4    C08_CS5   C08_CS6    C08_CS7    C08_CS8
## 1   145.25131   223.7655  251.2455   380.7940   259.0969
## 2   216.35336   600.3054  459.4174   558.8020   974.5694
## 3   186.02922   448.1481  620.2845   881.5853   738.9993
## 4   408.26222   509.2011  270.7288   832.0621   646.4813
## 5   614.58097   729.2055  331.8737   549.0257   778.4692
## 6   676.71252   760.2573  563.9271   743.5483  1123.6770
## 7  1785.47472  2786.1717 1549.6171  2378.2314  3642.7213
## 8    48.00000   104.0000  124.0000   200.0000   184.0000
## 9  8630.60453 15437.6017 7964.5133 15996.5794 16961.4616
## 10 1359.92836  3079.8702 2219.3613  3277.7336  3858.7154
## 11   24.82645   114.2017  114.2017   248.2645   104.2711
## 12  778.79732  1692.1665 1413.2480  2088.9298  2067.6493
## 13 4236.79443  6504.3040 4172.9710  5769.6155  7112.8355
## 14  336.00000  1084.0000  916.0000  1840.0000  1612.0000
## 15   43.22571   133.6067  263.2839   267.2135   263.2839
## 16  195.46378   549.7419  566.0305   789.9994   769.6386
## 17  692.11682  1319.1779  914.4838  1506.8716  1831.9141
## 18  354.99982   673.0346  662.3675  1138.0462   972.0006
## 19   90.09546   211.5285  152.7706   298.0418   380.2191
## 20  785.61458  2313.1329 1672.8122  2146.8257  3200.9753
## 21 1235.01644  2133.8041 1227.2317  1882.2404  2562.6611
## 22 1959.46192  3722.9151 2815.6525  3554.6276  5082.8933
## 23  716.98521  1306.0758  996.0281  1682.2772  1864.1999
## 24 1852.31160  2709.7794 1836.8577  2790.3848  3167.0027
## 25  237.89039   638.7264  498.8367   943.2416   907.0048
## 26  374.06166   871.4404  476.8259   887.8826   818.0030
## 27 1252.92208  1496.2424  808.1165  1354.0897  1690.5333
## 28 1170.05917  2597.9521 2443.1609  3857.8122  4354.8798
## 29 2924.74243  3124.7185 1241.8094  3696.2033  4327.3068
## 30 1483.30742  2111.6265 1126.3540  2406.8400  2507.0810
## 31  745.03620  1195.3682  525.5945  1082.6376  1293.4268
## 32  676.00000  1268.0000 1020.0000  1684.0000  2032.0000
## 33  159.22620   254.7619  167.1875   433.8914   346.3170
## 34  152.00000   212.0000  184.0000   248.0000   196.0000

mtq

## Simple feature collection with 34 features and 23 fields
## geometry type:  POLYGON
## dimension:      XY
## bbox:           xmin: 690574.4 ymin: 1592426 xmax: 736126.5 ymax: 1645660
## epsg (SRID):    32620
## proj4string:    +proj=utm +zone=20 +datum=WGS84 +units=m +no_defs
## First 10 features:
##    INSEE_COM               STATUT            LIBGEO P13_POP   C13_POP
## 1      97201       Commune simple L'Ajoupa-Bouillon    1830  1481.801
## 2      97202       Commune simple Les Anses-d'Arlet    3929  3190.115
## 3      97203       Commune simple      Basse-Pointe    3565  2983.215
## 4      97204       Commune simple         Le Carbet    3742  3157.044
## 5      97205       Commune simple       Case-Pilote    4464  3513.386
## 6      97206       Commune simple        Le Diamant    6063  4766.876
## 7      97207       Commune simple             Ducos   17051 14032.139
## 8      97208       Commune simple Fonds-Saint-Denis     813   684.000
## 9      97209 Préfecture de région    Fort-de-France   84174 68712.330
## 10     97210       Commune simple       Le François   18225 14959.798
##       C13_CS1    C13_CS2     C13_CS3   C13_CS4    C13_CS5   C13_CS6    C13_CS7
## 1    9.780866   48.90433    9.780866  102.6991   273.8642  288.5355   430.3581
## 2   97.433459  170.50855  109.612642  239.5239   560.2424  385.6741   746.5743
## 3   39.510829   98.77707   43.461911  181.7498   568.9559  565.0048   940.5055
## 4   80.133275  192.31986   84.139939  340.5664   532.8800  260.4331   989.5457
## 5   36.137682  172.65782  349.330931  517.9734   674.5701  317.2085   734.7995
## 6   28.374581  251.31772  397.190830  802.5953   835.0234  506.6890   956.6287
## 7   85.296622  614.27717  772.462370 2016.3061  2716.9554 1548.7246  2936.4613
## 8   32.000000   16.00000   12.000000   68.0000   112.0000  100.0000   224.0000
## 9   86.572838 2720.48912 4000.386802 8407.4236 13799.2254 7309.1357 16184.2574
## 10 137.873479  817.80956  544.951619 1470.5494  2966.3701 2115.8299  3577.5536
##       C13_CS8 P08_POP   C08_POP   C08_CS1    C08_CS2    C08_CS3   C08_CS4
## 1    317.8781    1691  1346.519  31.40569   43.18282   11.77713  145.2513
## 2    880.5453    3826  3067.742  49.00453  143.95079   65.33937  216.3534
## 3    545.2494    3804  3054.108  44.51803  106.84327   27.70011  186.0292
## 4    677.0259    3760  3038.656  88.93759  129.36377  153.61948  408.2622
## 5    710.7078    4515  3453.848  32.77765  155.69385  262.22121  614.5810
## 6    989.0568    5850  4569.721  33.41790  329.82460  338.35626  676.7125
## 7   3341.6553   16433 13441.442 106.52838  563.35180  629.34551 1785.4747
## 8    120.0000     873   708.000  16.00000   16.00000   16.00000   48.0000
## 9  16204.8388   89000 71566.825 119.06082 2480.10528 3976.89825 8630.6045
## 10  3328.8607   19189 15209.492 132.46653  666.44376  614.97272 1359.9284
##       C08_CS5   C08_CS6    C08_CS7    C08_CS8                       geometry
## 1    223.7655  251.2455   380.7940   259.0969 POLYGON ((699261.2 1637681,...
## 2    600.3054  459.4174   558.8020   974.5694 POLYGON ((709840 1599026, 7...
## 3    448.1481  620.2845   881.5853   738.9993 POLYGON ((706092.8 1642964,...
## 4    509.2011  270.7288   832.0621   646.4813 POLYGON ((697314.8 1623213,...
## 5    729.2055  331.8737   549.0257   778.4692 POLYGON ((702756.8 1617978,...
## 6    760.2573  563.9271   743.5483  1123.6770 POLYGON ((709840 1599026, 7...
## 7   2786.1717 1549.6171  2378.2314  3642.7213 POLYGON ((720449.9 1610106,...
## 8    104.0000  124.0000   200.0000   184.0000 POLYGON ((703159.7 1626214,...
## 9  15437.6017 7964.5133 15996.5794 16961.4616 POLYGON ((711183.1 1619627,...
## 10  3079.8702 2219.3613  3277.7336  3858.7154 POLYGON ((726831.3 1620678,...

Centroids

mtq_c <- st_centroid(mtq)
plot(st_geometry(mtq))
plot(st_geometry(mtq_c), add=TRUE, cex=1.2, col="red", pch=20)

Distances

mat <- st_distance(x=mtq_c,y=mtq_c)
mat[1:5,1:5]

## Units: [m]
##           [,1]     [,2]      [,3]      [,4]      [,5]
## [1,]     0.000 35297.56  3091.501 12131.617 17136.310
## [2,] 35297.557     0.00 38332.602 25518.913 18605.249
## [3,]  3091.501 38332.60     0.000 15094.702 20226.198
## [4,] 12131.617 25518.91 15094.702     0.000  7177.011
## [5,] 17136.310 18605.25 20226.198  7177.011     0.000

Polygons Aggregation, union :

mtq_u <- st_union(mtq)
plot(st_geometry(mtq), col="lightblue")
plot(st_geometry(mtq_u), add=T, lwd=2, border = "red")

Polygons Aggregation,

avec une variable de groupe :

library(dplyr)
mtq_u2 <- mtq %>% 
  group_by(STATUT) %>% 
  summarize(P13_POP=sum(P13_POP))
plot(st_geometry(mtq), col="lightblue")
plot(st_geometry(mtq_u2), add=T, lwd=2, border = "red", col=NA)

Buffer

mtq_b <- st_buffer(x = mtq_u, dist = 5000)
plot(st_geometry(mtq), col="lightblue")
plot(st_geometry(mtq_u), add=T, lwd=2)
plot(st_geometry(mtq_b), add=T, lwd=2, border = "red")

Polygon Intersection

m <- rbind(c(700015,1624212), c(700015,1641586), c(719127,1641586), 
           c(719127,1624212), c(700015,1624212))
p <- st_sf(st_sfc(st_polygon(list(m))), crs = st_crs(mtq))
plot(st_geometry(mtq))
plot(p, border="red", lwd=2, add=T)

Polygon Intersection

mtq_z <- st_intersection(x = mtq, y = p)
plot(st_geometry(mtq))
plot(st_geometry(mtq_z), col="red", border="green", add=T)

Autre traitements

• st_area(x)
• st_length(x)

Autre traitements

• st_disjoint(x, y, sparse = FALSE)
• st_touches(x, y, sparse = FALSE)
• st_crosses(s, s, sparse = FALSE)
• st_within(x, y, sparse = FALSE)
• st_contains(x, y, sparse = FALSE)
• st_overlaps(x, y, sparse = FALSE)
• st_equals(x, y, sparse = FALSE)
• st_covers(x, y, sparse = FALSE)
• st_covered_by(x, y, sparse = FALSE)
• st_covered_by(y, y, sparse = FALSE)
• st_equals_exact(x, y,0.001, sparse = FALSE)
• …

Jointure spatiale

• st_join

Voronoi Polygons

google: “st_voronoi R sf” (https://github.com/r-spatial/sf/issues/474 & https://stackoverflow.com/questions/45719790/create-voronoi-polygon-with-simple-feature-in-r)

mtq_v <- st_voronoi(x = st_union(mtq_c))
mtq_v <- st_intersection(st_cast(mtq_v), st_union(mtq))
mtq_v <- st_join(x = st_sf(mtq_v), y = mtq_c, join=st_intersects)
mtq_v <- st_cast(mtq_v, "MULTIPOLYGON")
plot(st_geometry(mtq_v), col='lightblue')

Ecrire des données

system("rm data/voronoi.geojson")
write_sf(mtq_v,"./data/voronoi.geojson",driver="GeoJSON")

Cartographie

Cartgographie avec ggplot

library(sf)
# Import geo layers
# Communes of Seine Maritime
sm <- st_read(dsn = "data/seine_maritime.geojson", 
              stringsAsFactors = F, quiet=TRUE)
# French departements
dep <- st_read(dsn = "data/dep.geojson", 
               stringsAsFactors = F, quiet=TRUE)
# change projection (lambert93)
sm <- st_transform(sm, 2154)
dep <- st_transform(dep, 2154)
# Import dataset  
csp <- read.csv("data/data_seine_maritime.csv")
# merge geolayer and dataset
sm <- merge(sm, csp, by="INSEE_COM", all.x=TRUE)

Cartgographie avec ggplot

• ?geom_sf
• ?geom_sf_label
• ?geom_sf_text
• ?coord_sf

Cartographie avec ggplot

library(ggplot2)
ggplot()+geom_sf(data=dep,fill="ivory",color="ivory3")+
  geom_sf_text(data=dep %>% filter(CODE_REG!=11),aes(label=CODE_DEPT),size=3,family="Palatino", fontface="bold")

Cartographie avec ggplot

library(ggplot2)
bb = st_bbox(sm)
ggplot()+geom_sf(data=dep,fill="ivory",color="ivory3")+
  geom_sf(data = sm %>% st_centroid,aes(size=act))+
  coord_sf(xlim=bb[c(1,3)],ylim=bb[c(2,4)],ndiscr = 0)

Cartographie avec ggplot

library(ggplot2)
bb = st_bbox(sm)
cols <- c("#e3b4a2", "#a2d5d6", "#debbd4", 
           "#afc2e3", "#b5dab6","#e9e2c1")
modlab <- c("Agriculteurs", "Artisans","Cadres", 
             "Employés","Prof. Inter.", "Ouvriers")
names(cols)=modlab

levels(sm$cat)=modlab
ggplot()+geom_sf(data=dep,fill="ivory",color="ivory3")+
  geom_sf(data = sm,aes(fill=cat),size=0.1)+
  scale_fill_manual("Dominant Socio-Professional\nCategory",values=cols)+
  theme_minimal()+
  coord_sf(xlim=bb[c(1,3)],ylim=bb[c(2,4)],ndiscr = 0)

Cartographie avec ggplot

Choroplethe et discretisation

Cartographie avec ggplot

hist(sm$cad/sm$act,25)

Cartographie avec ggplot

Carte plus complexes

library(sf)
# Import geo layers
# Communes of Seine Maritime
sm <- st_read(dsn = "data/seine_maritime.geojson", 
              stringsAsFactors = F, quiet=TRUE)
# French departements
dep <- st_read(dsn = "data/dep.geojson", 
               stringsAsFactors = F, quiet=TRUE)
# change projection (lambert93)
sm <- st_transform(sm, 2154)
dep <- st_transform(dep, 2154)
# Import dataset  
csp <- read.csv("data/data_seine_maritime.csv")
# merge geolayer and dataset
sm <- merge(sm, csp, by="INSEE_COM", all.x=TRUE)

Carte simple symboles proportionels

library(cartography)
plot(st_geometry(sm))
propSymbolsLayer(sm, var = "act")
title("Active Population")

Carte simple symboles proportionels

Carte symboles proportionels

# Custom map of active population
par(mar=c(0.2,0.2,1.4,0.2))
bb <- st_bbox(sm)
# the bbox is used to center the map on the Seine Maritime depatement
plot(st_geometry(dep), col = "ivory", border="ivory3",  bg="azure", 
     xlim = bb[c(1,3)], ylim =  bb[c(2,4)])
plot(st_geometry(sm), col="cornsilk2", border = NA, lwd = 0.5, add=T)
propSymbolsLayer(sm, var = "act", col="darkblue", inches = 0.6, 
                 border = "white", lwd=0.7, symbols = "square",
                 legend.style = "e", legend.pos="topleft",
                 legend.title.txt = "Labor Force\n(2014)", 
                 legend.values.rnd = 0)
# Scale Bar
barscale(size = 10)
# North Arrow
north(pos = "topright", col = "darkblue")
# Full layout
layoutLayer(title = "Workforce in Seine-Maritime", 
            sources = "Insee, 2018", author = "Kim & Tim, 2018", 
            col = "darkblue", coltitle = "white", tabtitle = TRUE, 
            frame = TRUE, scale = NULL, north = FALSE)
 
title("Active Population")

Carte symboles proportionels

Carte qualitative

#To display qualitative data modalities
mod <- c("agr", "art", "cad", "int", "emp", "ouv")
# labels in the legedn
modlab <- c("Agriculteurs", "Artisans","Cadres", 
            "Prof. Inter.", "Employés", "Ouvriers")
# colors
cols <- c("#e3b4a2", "#a2d5d6", "#debbd4", 
          "#b5dab6", "#afc2e3", "#e9e2c1")
par(mar=c(0.2,0.2,1.4,0.2))
plot(st_geometry(dep), col = "ivory", border="ivory3", bg="azure",
     xlim = bb[c(1,3)], ylim =  bb[c(2,4)])
typoLayer(sm, var = "cat", 
          border = "ivory", lwd = 0.5, 
          legend.values.order = mod,
          col = cols,
          add=TRUE, legend.pos = "n")
# functions are dedicated to legend display
legendTypo(title.txt = "Dominant Socio-Professional\nCategory", 
           col = cols, 
           categ = modlab, 
           nodata = F)
barscale(size = 10)
north(pos = "topright", col = "darkblue")
layoutLayer(title = "Workforce Distribution in Seine-Maritime", 
            sources = "Insee, 2018", author = "Kim & Tim, 2018", 
            col = "darkblue", coltitle = "white", tabtitle = TRUE,
            frame = TRUE, scale = NULL, north = FALSE)

Carte qualitative

Choroplete

# Compute the share of "managers" in the active population
sm$pcad <- 100 * sm$cad / sm$act

# The getBreaks() function is used to classify the variable
bks <- getBreaks(v = sm$pcad, method = "quantile", nclass = 6)

# The carto.pal() function give access to various palettes
cols <- carto.pal("green.pal", 3,"wine.pal",3)

# Create the map
par(mar=c(0.2,0.2,1.4,0.2))
plot(st_geometry(dep), col = "ivory", border="ivory3", bg="azure",
     xlim = bb[c(1,3)], ylim =  bb[c(2,4)])
choroLayer(sm, var = "pcad", breaks = bks, 
           col = cols, border = "grey80", 
           legend.values.rnd = 1,
           lwd = 0.4, legend.pos = "topleft", 
           legend.title.txt = "Share of managers (%)", add=T)
# Add a layout
layoutLayer(title = "Managers", 
            sources = "Insee, 2018", author = "Kim & Tim, 2018", 
            theme = "green.pal", 
            col = "darkred", coltitle = "white", 
            tabtitle = TRUE, 
            frame = TRUE, scale = 10)
north(pos = "topright")

Choroplethe

Carte interactives avec Leaflet

library(leaflet)
sm.center.4326 = sm %>% st_centroid()%>% st_transform(4326)
leaflet(data = sm.center.4326 ) %>% 
  addTiles() %>% 
  addCircleMarkers(radius =~ sqrt(act/100)*1.5,
                   fillColor = "#449944",
                   stroke=FALSE,
                   fillOpacity = 1,
                   popup = ~paste(LIBELLE,":",act,"actifs"))

https://rstudio.github.io/leaflet/

• addMarkers
• addCircleMarkers
• addPolygons
• …..

Carte interactives avec Leaflet

Exercice

Charger les contours des départements français contenus dans le répertoire exo6_dep

Calculer à partir des données communales contenues dans le fichier exo6_data.csv des taux de naissances par départements.

Joindre les deux tables et vérifier ques des données sont associées à chaque départements.

Corriger les problèmes de jointure éventuels.

Exporter les données en geojson

Réaliser une carte choroplèthe avec ces données.

Exercice

Calculer et afficher les voronois associés aux stations velib de new-york.

Les données sont disponnibles dans le fichiers json ./data/input_NewYork.json

Créer une data.frame avec les latitudes, longitudes et nbr de vélos des stations

Utiliser la fonction st_as_sf avec l’option coords pour transformer celle-ci en data.frame spatiale.

Exercice

Faire une carte interactive des monuments historiques à paris

Faire une carte en symbol proportionel avec le nombre de monuments par iris.

regarder les fonctions st_contains,st_within

! vous travaillerez avec des données en lambert 93

Calculer la densité de monuments par hectare pour chaque iris.

Faire une carte choroplète

Les contours des iris sont disponnibles dans le répertoire “data/CONTOURS-IRIS/”

Les données sont disponibles dans le répertoire “data/monuments_paris.geojson”

Exercice

Faire une carte en symboles proportionels du nombre de vélos dans les stations vélib à NewYork.

Utiliser un fond de carte open street map avec la library cartography.

Informations et exercices supplémentaires

(dépot staRday)[http://github.comeetie.fr/satRday]